Rumi Chunara

Associate Professor, Biostatistics and Computer Science & Engineering

Director, Center for Health Data Science

New York University, School of Global Public Health and
Tandon School of Engineering

Publications | Group | Teaching | Awards | Press

I am an Associate Professor at New York University, Director of the Center for Health Data Science, and Director of the AI and Emerging Technologies Master's Program. My research develops computational methods to evaluate, deploy, and govern AI systems in real-world environments, particularly in healthcare, public health, and public-sector settings.

My group works at the intersection of artificial intelligence, health, climate, and society. We study how AI systems behave across populations, institutions, and deployment contexts, with a particular focus on robustness, fairness, reasoning, and decision-making under real-world constraints. Our work combines methodological advances in machine learning with collaborations involving healthcare systems, governments, community organizations, and international partners.

Current areas of focus include:

A central theme across this work is moving beyond benchmark performance to understand how AI systems function under the heterogeneity, uncertainty, and operational constraints that characterize real-world environments. Ultimately, I study, design and show how AI can be designed, evaluated, and deployed to improve decision-making for individuals, organizations, and communities.


Education and Capacity Building

My work increasingly informs decision-making beyond academia through collaborations with healthcare systems, city agencies, and international organizations. Recent activities include advisory and strategy engagements with NYC Health + Hospitals, UNFPA, the Public Health Agency of Canada, the Wellcome Trust and the National Institutes of Health (NHLBI AI Working Group, All of Us Resource Access Board) on topics spanning AI, population data, healthcare delivery, and public health.


In recent years, I have also developed a body of work related to cardiovascular disease (JACC 2023, Prog Card Dis 2023, Prev Med 2022) and best practices for teaching in Health Data Science (Harvard Data Sci Review 2022, Lancet Global Health 2023). Please see my Google Scholar page for a full list of publications.


Selected Awards and Honors

Selected Press